The use of social network analysis software to analyze communication patterns and interaction in online collaborative environments

Social network analysis software such as NodeXL has been used to describe participation and interaction in numerous social networks but has not yet been widely used to examine dynamics in online classes, where participation is frequently required rather than optional and participation patterns may be impacted by instructor requirements as well as participants’ intrinsic engagement with the subject matter. Such analysis can be valuable in programs focused on teaching collaborative and communicative skills, including teacher preparation programs, to provide information about instructional practices likely to facilitate student interaction and collaboration across diverse student populations. This exploratory study used NodeXL to visualize students’ participation in an online course, with the goal of identifying (1) ways in which NodeXL could be used to describe patterns in participant interaction within an instructional setting and (2) identifying specific patterns in participant interaction among students in this particular course. In this sample, general education teachers demonstrated higher measures of connection and interaction with other participants than did those from specialist (ESOL or special education) backgrounds, and tended to interact more frequently with all participants than the majority of participants from specialist backgrounds. We recommend further research to delineate specific applications of NodeXL within an instructional context, particularly to identify potential patterns in student participation based on variables such as gender, background, cultural and linguistic heritage, prior training and education, and prior experience so that instructors can ensure their practice helps to facilitate student interaction in light of each of these potential variables.

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